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Agriculture
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Research on Plant Production in Greenhouse and Plant Factory Systems
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Research on Plant Production in Greenhouse and Plant Factory Systems

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".

Deadline for manuscript submissions: 15 January 2025 | Viewed by 5139

Special Issue Editor

Dr. Wei Lu

E-Mail Website
Guest Editor
College of Horticulture, Sichuan Agricultural University, Chengdu 613000, China
Interests: design and intelligent control of plant production system; greenhouse; controlled environment; energy saving; aerodynamics; vertical farming

Special Issue Information

Dear Colleagues,

Due to the effects of uncertain climate factors in crop growth, advanced technologies have come to play an increasingly significant role in agricultural production. An intelligent greenhouse and plant factory system, in combination with the greenhouse and plant factory, intelligent equipment such as sensors, and the Internet of Things, successfully optimizes the crop growth environment. Through precise monitoring of crop growth conditions such as temperature, moisture, sunlight, etc., agricultural workers can adjust the indoor artificial lights and control the irrigation frequency to improve crop photosynthesis and water use efficiency, improving the yield and quality of fruits and vegetables. Compared with traditional greenhouses, intelligent, automated, and scientific greenhouses and plant factories have become indispensable parts of modern agriculture. However, intelligent greenhouse and plant factory systems are inevitably characterized by high costs and difficult operations, preventing many farmers from taking advantage of the convenience they offer.

This Special Issue will collect a range of articles and reviews associated with the greenhouse and plant factory environmental control system and smart farming. Potential topics include (but are not limited to):

  • Greenhouse and plant factory environment simulation;
  • Temperature and heat control;
  • Sunlight control and artificial light applications;
  • Water use monitoring and irrigation management;
  • Crop nutrient monitoring and sustainable fertilization;
  • The design and operation of smart greenhouse and plant factory systems;
  • The economic and biological benefits of intelligent greenhouse and plant factory production.

We look forward to receiving your contributions.

Dr. Wei Lu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • greenhouse
  • plant factory
  • controlled environment
  • precision agriculture
  • artificial light
  • environment simulation

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

21 pages, 7327 KiB  
Article
Design and Thermal-Optical Environment Simulation of Double-Slope Greenhouse Roof Structure Based on Ecotect
by Xuanhe Yang and Yunfei Ma
Agriculture 2024, 14(8), 1410; https://doi.org/10.3390/agriculture14081410 - 20 Aug 2024
Viewed by 509
Abstract
At present, most double-slope greenhouse shade systems utilize insulation quilts on a portion of the roof to enhance the light and thermal environment for winter production. However, this method often leads to challenges such as uneven light distribution and significant heat dissipation. To [...] Read more.
At present, most double-slope greenhouse shade systems utilize insulation quilts on a portion of the roof to enhance the light and thermal environment for winter production. However, this method often leads to challenges such as uneven light distribution and significant heat dissipation. To improve the uniformity of light distribution and optimize the light and thermal environment inside a shade room, this study employed Ecotect software 2011 for simulating and analyzing the light and thermal conditions of a double-slope greenhouse shade system. The study aimed to investigate the optimal spacing and width of roof windows. The results demonstrated that a double-slope greenhouse with roof windows of 300 mm width spaced at 3000 mm intervals achieved optimal performance. This configuration yielded a light distribution uniformity of 74.4% and an average temperature of 8.1 °C. Such conditions are conducive to creating an environment suitable for cultivating edible mushrooms, thereby enhancing the quality and consistency of mushroom production. This paper provides an effective method for designing the roof structure of double-slope greenhouses to enhance light capture, thermal regulation, and energy efficiency. Full article
(This article belongs to the Special Issue Research on Plant Production in Greenhouse and Plant Factory Systems)
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19 pages, 6038 KiB  
Article
Establishment and Solution of a Finite Element Gas Exchange Model in Greenhouse-Grown Tomatoes for Two-Dimensional Porous Media with Light Quantity and Light Direction
by Chengyao Jiang, Ke Xu, Jiahui Rao, Jiaming Liu, Yushan Li, Yu Song, Mengyao Li, Yangxia Zheng and Wei Lu
Agriculture 2024, 14(8), 1209; https://doi.org/10.3390/agriculture14081209 - 23 Jul 2024
Cited by 1 | Viewed by 558
Abstract
An accurate gas utilization model is essential for precisely detecting plant photosynthetic capacity. Existing equipment for measuring the plant photosynthetic rate typically considers the key parameters of mesophyll cell conductance and a photosynthetic model based on the carbon reaction process under direct light [...] Read more.
An accurate gas utilization model is essential for precisely detecting plant photosynthetic capacity. Existing equipment for measuring the plant photosynthetic rate typically considers the key parameters of mesophyll cell conductance and a photosynthetic model based on the carbon reaction process under direct light conditions. However, the light environment signals received by the plant canopy not only vary significantly in incidence angles, but the effective light intensity also differs greatly from the measured values under vertical incidence conditions. To reduce the deviation between existing photosynthetic models and the actual photosynthetic efficiency of leaves, this study employs the gas diffusion method from engineering, using the finite element approach. Based on elastic mechanics and seepage mechanics, the internal stress field control equation of tomato leaves and the two-phase flow equation under a CO2 porous medium were derived. A mathematical model of porous gas–liquid two-phase fluid-solid coupling was established, solved, and analyzed. Preliminary verification was conducted through tests. The results show that in the initial stage of CO2 entering the leaf, the gas flow velocity is higher because of the larger pressure gradient between the pore and the leaf. In this stage, the gas diffusion rate is higher. As the intake time increases, the pressure gradient gradually decreases, and the inlet velocity slows down. Consequently, the diffusion rate gradually reduces. Because of the coupling of light quantity and light direction, the gas diffusion rate significantly increases compared with the uncoupled model. Additionally, a diffusion model that does not consider fluid–solid coupling will overestimate the gas flow rate as the depth of gas entry increases. Therefore, the internal gas diffusion model must account for the effect of coupling on the diffusion rate. Full article
(This article belongs to the Special Issue Research on Plant Production in Greenhouse and Plant Factory Systems)
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16 pages, 3734 KiB  
Article
Computational Fluid Dynamics Model with Realistic Plant Structures to Study Airflow in and around a Plant Canopy on a Cultivation Shelf in a Plant Factory with Artificial Light
by Xuan Gu and Eiji Goto
Agriculture 2024, 14(7), 1199; https://doi.org/10.3390/agriculture14071199 - 21 Jul 2024
Viewed by 1290
Abstract
Airflow plays a crucial role in plant growth because it supplies CO2, O2, and energy to plants in a plant factory with artificial light (PFAL). Therefore, understanding how various factors affect airflow in and around a plant canopy is [...] Read more.
Airflow plays a crucial role in plant growth because it supplies CO2, O2, and energy to plants in a plant factory with artificial light (PFAL). Therefore, understanding how various factors affect airflow in and around a plant canopy is essential. In this study, we developed a computational fluid dynamics (CFD) model with realistic plant structures created using structure-from-motion imaging to investigate airflow in and around a plant canopy. The averages of the absolute percentage errors of simulated air velocity in three conditions were 6.7%, 10.1%, 12.7%, respectively. The simulated and measured air velocities agreed well, confirming the accuracy of the developed CFD model. The effects of inflow velocities and plant canopy structures on the airflow in and around the plant canopy were analysed using the validated CFD model. The inflow velocities significantly decreased stagnant zones (from 62.4% to 7.2%) and increased the airflow uniformity in and around the plant canopy. A staggered layout of the plant canopy slightly decreased stagnant zones (from 16.4% to 13.2%) and increased the airflow uniformity. The airflow in and around the plant canopy was further inhibited by a large plant structure. This CFD model provided a basis for improving the airflow status in and around a plant canopy in a PFAL. Full article
(This article belongs to the Special Issue Research on Plant Production in Greenhouse and Plant Factory Systems)
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21 pages, 22046 KiB  
Article
An Integrated IoT Sensor-Camera System toward Leveraging Edge Computing for Smart Greenhouse Mushroom Cultivation
by Hoang Hai Nguyen, Dae-Yun Shin, Woo-Sung Jung, Tae-Yeol Kim and Dae-Hyun Lee
Agriculture 2024, 14(3), 489; https://doi.org/10.3390/agriculture14030489 - 18 Mar 2024
Viewed by 1978
Abstract
Industrial greenhouse mushroom cultivation is currently promising, due to the nutritious and commercial mushroom benefits and its convenience in adapting smart agriculture technologies. Traditional Device-Cloud protocol in smart agriculture wastes network resources when big data from Internet of Things (IoT) devices are directly [...] Read more.
Industrial greenhouse mushroom cultivation is currently promising, due to the nutritious and commercial mushroom benefits and its convenience in adapting smart agriculture technologies. Traditional Device-Cloud protocol in smart agriculture wastes network resources when big data from Internet of Things (IoT) devices are directly transmitted to the cloud server without processing, delaying network connection and increasing costs. Edge computing has emerged to bridge these gaps by shifting partial data storage and computation capability from the cloud server to edge devices. However, selecting which tasks can be applied in edge computing depends on user-specific demands, suggesting the necessity to design a suitable Smart Agriculture Information System (SAIS) architecture for single-crop requirements. This study aims to design and implement a cost-saving multilayered SAIS architecture customized for smart greenhouse mushroom cultivation toward leveraging edge computing. A three-layer SAIS adopting the Device-Edge-Cloud protocol, which enables the integration of key environmental parameter data collected from the IoT sensor and RGB images collected from the camera, was tested in this research. Implementation of this designed SAIS architecture with typical examples of mushroom cultivation indicated that low-cost data pre-processing procedures including small-data storage, temporal resampling-based data reduction, and lightweight artificial intelligence (AI)-based data quality control (for anomalous environmental conditions detection) together with real-time AI model deployment (for mushroom detection) are compatible with edge computing. Integrating the Edge Layer as the center of the traditional protocol can significantly save network resources and operational costs by reducing unnecessary data sent from the device to the cloud, while keeping sufficient information. Full article
(This article belongs to the Special Issue Research on Plant Production in Greenhouse and Plant Factory Systems)
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